Series de tiempo: Tarea 2
Guillermo Alberto Garcia Candanosa - A01034958
2022-05-23
- Carga la librería fpp2 y utiliza la información de los primeros 20 días de la base de datos correspondiente a la demanda diaria de electricidad de Victoria, en Australia, para 2014 (datos20 <- head(elecdaily,20))
Carga de librerías:
library(fpp2)
library(fpp3)
library(forecast)
library(readxl)
library(TSstudio)
library(ggseas)
library(data.table)
library(urca)
library(formattable)
library(janitor)Carga de base de datos:
datos20 <-
head(elecdaily,20)- Grafica la serie de tiempo.
autoplot(datos20[,"Demand"]) +
ggtitle("Total electricity demand in GW for Victoria, Australia, every day during 2014") +
xlab("Time") +
ylab("Total electricity demand [GW]")
- Has un modelo de regresión lineal con las variables disponibles en la base de datos, a fin de pronosticar la demanda de electricidad.
# Transformación de datos a tsibble
datos20_tbl <-
as_tsibble(datos20,
pivot_longer = FALSE)
# Regresión lineal múltiple en datos ts
fit.datos20 <- tslm(Demand ~
Temperature + WorkDay,
data = datos20)
summary(fit.datos20)##
## Call:
## tslm(formula = Demand ~ Temperature + WorkDay, data = datos20)
##
## Residuals:
## Min 1Q Median 3Q Max
## -35.670 -14.041 5.072 15.947 29.648
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 41.1689 17.3294 2.376 0.0295 *
## Temperature 6.2842 0.6592 9.533 3.1e-08 ***
## WorkDay 17.5890 11.1214 1.582 0.1322
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.14 on 17 degrees of freedom
## Multiple R-squared: 0.888, Adjusted R-squared: 0.8749
## F-statistic: 67.42 on 2 and 17 DF, p-value: 8.263e-09# Regresión lineal múltiple en tsibble
fit.datos20_tbl <- datos20_tbl %>%
model(
TSLM(Demand ~
Temperature + WorkDay)
)
report(fit.datos20_tbl)## Series: Demand
## Model: TSLM
##
## Residuals:
## Min 1Q Median 3Q Max
## -35.670 -14.041 5.072 15.947 29.648
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 41.1689 17.3294 2.376 0.0295 *
## Temperature 6.2842 0.6592 9.533 3.1e-08 ***
## WorkDay 17.5890 11.1214 1.582 0.1322
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 21.14 on 17 degrees of freedom
## Multiple R-squared: 0.888, Adjusted R-squared: 0.8749
## F-statistic: 67.42 on 2 and 17 DF, p-value: 8.2627e-09#Gráfica de observaciones reales y estimados con Regresión Lineal Múltiple
autoplot(datos20[,"Demand"], series = "Data") +
autolayer(fitted(fit.datos20), series = "Fitted") +
xlab("Day") +
ylab("") +
ggtitle("Total electricity demand in GW for Victoria, Australia, every day during 2014") +
guides(colour = guide_legend(title = ""))
Interpreta los coeficientes de tu regresión. R: En Victoria, Australia; un grado Celsius adicional en la temperatura máxima se traduce en un incremento de 6.28 GW en la demanda diaria de electricidad. La variable WorkDay, que señala si se hace referencia a días hábiles o inhábiles, no es estadísticamente significativa.
Analiza los residuales: grafícalos e interprétalos.
# Gráfica de los residuales
fit.datos20_tbl %>% gg_tsresiduals()
# La primera gráfica nos sugiere que los residuales podrían no estarse comportando de forma aleatoria, pues hay una tendencia alcista en los mismos.
# Prueba Ljung-Box
## Hipótesis nula: serie estacionaria
## Hipótesis alternativa: serie NO estacionaria
augment(fit.datos20_tbl) %>%
features(.innov, ljung_box,
lag = ifelse(2*7 > nrow(datos20_tbl)/5,
nrow(datos20_tbl)/5,
2*7), # De acuerdo con el libro de texto FPP3, se utiliza el número de observaciones dividido entre 5 si este resultado es menor que 10 o que 2m (cuando la serie tiene estacionalidad y m es el periodo de estacionalidad.)
dof = 2) # Número de parámetros del modelo.# Gráfico entre las variables independientes y los residuales
datos20_tbl %>%
left_join(residuals(fit.datos20_tbl),
by = "index") %>%
pivot_longer(WorkDay:Temperature,
names_to = "regressor",
values_to = "x") %>%
ggplot(aes(x = x, y = .resid)) +
geom_point() +
facet_wrap(. ~ regressor, scales = "free_x") +
labs(y = "Residuals", x = "")
# Gráfico entre valores estimados y residuales
augment(fit.datos20_tbl) %>%
ggplot(aes(x = .fitted, y = .resid)) +
geom_point() +
labs(x = "Fitted", y = "Residuals")
R: A partir de la gráfica de residuales, se sugiere que quizás los mismos tienen una tendencia. El correlograma no sugiere que haya correlaciones estadísticamente significativas entre los diferentes lags utilizados, y el histograma sugiere que pudiera haber una distribución que se aproxime a la distribución normal de los mismos residuales. Al llevar a cabo la prueba Ljung-Box, considerando que el pvalue es mayor a 0.05, concluimos que la hipótesis nula se acepta, por lo tanto la serie es estacionaria. No se aprecia que exista correlación alguna entre las variables independientes y los residuales, ni tampoco entre las estimaciones y los residuales.
- Utiliza tu moldeo para pronosticar la demanda de electricidad, para el siguiente día, si la temperatura fuera de 15° grados y compáralo con el pronóstico de 35°. ¿Cuáles son los pronósticos? ¿Parecen realistas?
# Genero escenarios para pronosticar la demanda de energía eléctricica considerando que el día siguiente es un día hábil con 15° o con 35° de temperatura.
future_scenarios <- scenarios(
LowTemp = new_data(datos20_tbl, 1) %>%
mutate(WorkDay = 1,
Temperature = 15),
HiTemp = new_data(datos20_tbl, 1) %>%
mutate(WorkDay = 1,
Temperature = 35),
names_to = "Scenario"
)
# Hago los pronósticos correspondientes a cada escenario
fc <- forecast(fit.datos20_tbl,
new_data = future_scenarios)
# Genero las gráficas de los pronósticos.
datos20_tbl %>%
autoplot(Demand) +
autolayer(fc) +
labs(title = "Total electricity demand in GW for Victoria, Australia",
y = "Electricity demand [GW]")
R: El pronóstico de la demanda de energía eléctrica para el día siguiente asumiendo que la temperatura máxima es de 15°, si bien es consistente con la tendencia del comportamiento de los datos, no se podría afirmar que es un comportamiento realista. Esto pues no se cuenta con ningún registro dentro del dataframe datos20 que corresponda a dicha temperatura máxima. Por lo tanto, para hacer ese pronóstico, se tendría que suponer que el comportamiento de los datos de demanda de electricidad vs temperatura máxima seguiría manteniendo una tendencia lineal en esos niveles de temperatura. Para el pronóstico de 35°, por otro lado, si se cuenta con registros que rodean esta temperatura máxima; y dichos registros efectivamente rodean también el pronóstico de demanda de electricidad. Por lo tanto, este pronóstico parece una aproximación realista considerando que esa fuera la temperatura máxima para ese día.
- Obtén las mediciones de error del modelo y comenta si los resultados son útiles. ¿Son mejores que si usamos el método naive?
# Calculo porcentaje de error de pronóstico considerando que al siguiente día la temperatura sería 15°C
error.15 <-
formattable::percent(
(fc[1,5] - elecdaily[21,1])/
elecdaily[21,1]
)
view(error.15)
# Calculo porcentaje de error de pronóstico considerando que al siguiente día la temperatura sería 35°C
error.35 <-
formattable::percent(
(fc[2,5] - elecdaily[21,1])/
elecdaily[21,1]
)
view(error.35)
# Realizo el modelo NAIVE
naive_model <-
datos20_tbl %>%
model(
naive = NAIVE(Demand)
)
# Calculo el pronóstico del modelo NAIVE
naive_forecast <-
naive_model %>%
forecast(h=1)
# Genero las gráficas del pronóstico con el modelo NAIVE.
datos20_tbl %>%
autoplot(Demand) +
autolayer(naive_forecast) +
labs(title = "Total electricity demand in GW for Victoria, Australia",
y = "Electricity demand [GW]")
# Calculo porcentaje de error de pronóstico considerando el modelo NAIVE
error.naive <-
formattable::percent(
(naive_forecast[1,4] - elecdaily[21,1])/
elecdaily[21,1]
)
View(error.naive)R: Los resultados de la regresión no resultan ser tan útiles como el modelo NAIVE en este caso, pues las estimaciones de temperatura que se utilizaron para el siguiente día con la regresión fueron de 15°C y de 35°C cuando la temperatura máxima real fue en realidad de 23.1°C. Con esto, el método NAIVE de utilizar la última observación como pronóstico resultó más acertado que la regresión lineal, con un porcentaje de error del 2.75% a comparación de los errores de 31.19% y 25.34% para los pronósticos de la regresion lineal a 15°C y a 35°C respectivamente.
- Carga la base de datos “Elecmensual 20190618”; separa los componentes de la serie de tiempo e incluye la gráfica (es la demanda mensual ficticia de electricidad de Victoria, en Australia, desde enero de 1950).
# Carga de la base de datos en ts
Elecmensual_20190618.xls <-
read_excel("Elecmensual 20190618.xlsx") %>%
select(Demand)
Elecmensual_20190618.ts <-
ts(
Elecmensual_20190618.xls,
start = c(1950,1),
deltat = 1/12
)
# Grafico la serie de tiempo original
ts_plot(Elecmensual_20190618.ts[,"Demand"],
slider = TRUE,
type = "multiple",
title = "Demanda mensual de electricidad de Victoria, en Australia, desde enero de 1950",
Ytitle = "Demanda de electricidad [GW]",
Xtitle = "Mes"
)# Descompongo la serie de tiempo en forma aditiva y multiplicativa
ts_decompose(Elecmensual_20190618.ts[,"Demand"], type = "both")# Ajusto formato de serie de tiempo a data.table
Elecmensual_20190618.dt <- as.data.table(Elecmensual_20190618.ts)
# Ajusto los números de meses a fechas según la descripción provista
Elecmensual_20190618.dt <- Elecmensual_20190618.dt %>%
mutate(Month =
yearmonth(
seq(
as.Date("1950-01-01"),
by = "month",
length.out = 730
)
)
)
# Tendencia
Elecmensual_20190618.dt[,trend := zoo::rollmean(Demand, 12, fill=NA, align = "right")]## Warning in `[.data.table`(Elecmensual_20190618.dt, , `:=`(trend,
## zoo::rollmean(Demand, : Invalid .internal.selfref detected and fixed by taking
## a (shallow) copy of the data.table so that := can add this new column by
## reference. At an earlier point, this data.table has been copied by R (or was
## created manually using structure() or similar). Avoid names<- and attr<- which
## in R currently (and oddly) may copy the whole data.table. Use set* syntax
## instead to avoid copying: ?set, ?setnames and ?setattr. If this message doesn't
## help, please report your use case to the data.table issue tracker so the root
## cause can be fixed or this message improved.knitr::kable(tail(Elecmensual_20190618.dt))| Demand | Month | trend |
|---|---|---|
| 178.8567 | 2010 may. | 217.4504 |
| 185.7280 | 2010 jun. | 212.9069 |
| 200.5128 | 2010 jul. | 209.3583 |
| 203.2730 | 2010 ago. | 207.4522 |
| 198.2401 | 2010 sep. | 204.9424 |
| 198.3702 | 2010 oct. | 203.3041 |
# Datos sin la tendencia
Elecmensual_20190618.dt[,`:=`( detrended_a = Demand - trend, detrended_m = Demand / trend )]
knitr::kable(tail(Elecmensual_20190618.dt))| Demand | Month | trend | detrended_a | detrended_m |
|---|---|---|---|---|
| 178.8567 | 2010 may. | 217.4504 | -38.593708 | 0.8225172 |
| 185.7280 | 2010 jun. | 212.9069 | -27.178942 | 0.8723436 |
| 200.5128 | 2010 jul. | 209.3583 | -8.845483 | 0.9577495 |
| 203.2730 | 2010 ago. | 207.4522 | -4.179183 | 0.9798547 |
| 198.2401 | 2010 sep. | 204.9424 | -6.702250 | 0.9672969 |
| 198.3702 | 2010 oct. | 203.3041 | -4.933950 | 0.9757312 |
# Estacionalidad
Elecmensual_20190618.dt[,`:=`(seasonal_a = mean(detrended_a, na.rm = TRUE),
seasonal_m = mean(detrended_m, na.rm = TRUE)),
by=.(month(Month)) ]
knitr::kable(tail(Elecmensual_20190618.dt))| Demand | Month | trend | detrended_a | detrended_m | seasonal_a | seasonal_m |
|---|---|---|---|---|---|---|
| 178.8567 | 2010 may. | 217.4504 | -38.593708 | 0.8225172 | -2.4727042 | 0.9893817 |
| 185.7280 | 2010 jun. | 212.9069 | -27.178942 | 0.8723436 | -1.3238808 | 0.9951545 |
| 200.5128 | 2010 jul. | 209.3583 | -8.845483 | 0.9577495 | 0.8239771 | 1.0044215 |
| 203.2730 | 2010 ago. | 207.4522 | -4.179183 | 0.9798547 | 1.1708394 | 1.0051108 |
| 198.2401 | 2010 sep. | 204.9424 | -6.702250 | 0.9672969 | 1.8524413 | 1.0076365 |
| 198.3702 | 2010 oct. | 203.3041 | -4.933950 | 0.9757312 | -0.6260301 | 0.9977708 |
# Parte aleatoria
Elecmensual_20190618.dt[,`:=`( residual_a = detrended_a - seasonal_a,
residual_m = detrended_m / seasonal_m )]
knitr::kable(tail(Elecmensual_20190618.dt))| Demand | Month | trend | detrended_a | detrended_m | seasonal_a | seasonal_m | residual_a | residual_m |
|---|---|---|---|---|---|---|---|---|
| 178.8567 | 2010 may. | 217.4504 | -38.593708 | 0.8225172 | -2.4727042 | 0.9893817 | -36.121004 | 0.8313447 |
| 185.7280 | 2010 jun. | 212.9069 | -27.178942 | 0.8723436 | -1.3238808 | 0.9951545 | -25.855061 | 0.8765911 |
| 200.5128 | 2010 jul. | 209.3583 | -8.845483 | 0.9577495 | 0.8239771 | 1.0044215 | -9.669460 | 0.9535335 |
| 203.2730 | 2010 ago. | 207.4522 | -4.179183 | 0.9798547 | 1.1708394 | 1.0051108 | -5.350023 | 0.9748723 |
| 198.2401 | 2010 sep. | 204.9424 | -6.702250 | 0.9672969 | 1.8524413 | 1.0076365 | -8.554691 | 0.9599661 |
| 198.3702 | 2010 oct. | 203.3041 | -4.933950 | 0.9757312 | -0.6260301 | 0.9977708 | -4.307920 | 0.9779111 |
# Gráficas
ggsdc(Elecmensual_20190618.dt,
aes(x = Month, y = Demand),
method = "decompose",
frequency = 12,
s.window = 8,
type = "additive") +
geom_line() +
ggtitle("Aditiva") +
theme_minimal()## Warning in if (class(data[, xvar]) == "Date" & (is.null(frequency))) {: la
## condición tiene longitud > 1 y sólo el primer elemento será usado## Warning: Removed 6 row(s) containing missing values (geom_path).
ggsdc(Elecmensual_20190618.dt,
aes(x = Month, y = Demand),
method = "decompose",
frequency = 12,
s.window = 8,
type = "multiplicative") +
geom_line() +
ggtitle("Multiplicativa") +
theme_minimal()## Warning in if (class(data[, xvar]) == "Date" & (is.null(frequency))) {: la
## condición tiene longitud > 1 y sólo el primer elemento será usado
## Warning in if (class(data[, xvar]) == "Date" & (is.null(frequency))) {: Removed
## 6 row(s) containing missing values (geom_path).
#¿Es aditiva o multiplicativa?
ggAcf(Elecmensual_20190618.dt$residual_a)
ggAcf(Elecmensual_20190618.dt$residual_m)
Elecmensual_20190618.dt$residual_a %>% ur.kpss() %>% summary()##
## #######################
## # KPSS Unit Root Test #
## #######################
##
## Test is of type: mu with 6 lags.
##
## Value of test-statistic is: 0.0457
##
## Critical value for a significance level of:
## 10pct 5pct 2.5pct 1pct
## critical values 0.347 0.463 0.574 0.739Elecmensual_20190618.dt$residual_m %>% ur.kpss() %>% summary()##
## #######################
## # KPSS Unit Root Test #
## #######################
##
## Test is of type: mu with 6 lags.
##
## Value of test-statistic is: 0.0587
##
## Critical value for a significance level of:
## 10pct 5pct 2.5pct 1pct
## critical values 0.347 0.463 0.574 0.739# Carga de la base de datos en ts
Elecmensual_20190618.xls <-
read_excel("Elecmensual 20190618.xlsx") %>%
select(Demand)
Elecmensual_20190618.ts <-
ts(
Elecmensual_20190618.xls,
start = c(1950,1),
deltat = 1/12
)
Elecmensual_20190618.ts.trans <-
log(Elecmensual_20190618.ts,
base = 10)
# Ajusto formato de serie de tiempo a data.table
Elecmensual_20190618.dt.trans <- as.data.table(Elecmensual_20190618.ts.trans)
# Ajusto los números de meses a fechas según la descripción provista
Elecmensual_20190618.dt.trans <- Elecmensual_20190618.dt.trans %>%
mutate(Month =
yearmonth(
seq(
as.Date("1950-01-01"),
by = "month",
length.out = 730
)
)
)
# Tendencia
Elecmensual_20190618.dt.trans[,trend := zoo::rollmean(Demand, 12, fill=NA, align = "right")]## Warning in `[.data.table`(Elecmensual_20190618.dt.trans, , `:=`(trend,
## zoo::rollmean(Demand, : Invalid .internal.selfref detected and fixed by taking
## a (shallow) copy of the data.table so that := can add this new column by
## reference. At an earlier point, this data.table has been copied by R (or was
## created manually using structure() or similar). Avoid names<- and attr<- which
## in R currently (and oddly) may copy the whole data.table. Use set* syntax
## instead to avoid copying: ?set, ?setnames and ?setattr. If this message doesn't
## help, please report your use case to the data.table issue tracker so the root
## cause can be fixed or this message improved.knitr::kable(tail(Elecmensual_20190618.dt.trans))| Demand | Month | trend |
|---|---|---|
| 2.252505 | 2010 may. | 2.335101 |
| 2.268877 | 2010 jun. | 2.325785 |
| 2.302142 | 2010 jul. | 2.318815 |
| 2.308080 | 2010 ago. | 2.314956 |
| 2.297191 | 2010 sep. | 2.309837 |
| 2.297476 | 2010 oct. | 2.306418 |
# Datos sin la tendencia
Elecmensual_20190618.dt.trans[,`:=`( detrended_a = Demand - trend )]
knitr::kable(tail(Elecmensual_20190618.dt.trans))| Demand | Month | trend | detrended_a |
|---|---|---|---|
| 2.252505 | 2010 may. | 2.335101 | -0.0825954 |
| 2.268877 | 2010 jun. | 2.325785 | -0.0569078 |
| 2.302142 | 2010 jul. | 2.318815 | -0.0166733 |
| 2.308080 | 2010 ago. | 2.314956 | -0.0068766 |
| 2.297191 | 2010 sep. | 2.309837 | -0.0126460 |
| 2.297476 | 2010 oct. | 2.306418 | -0.0089413 |
# Estacionalidad
Elecmensual_20190618.dt.trans[,`:=`(seasonal_a = mean(detrended_a, na.rm = TRUE)
),
by=.(month(Month)) ]
knitr::kable(tail(Elecmensual_20190618.dt.trans))| Demand | Month | trend | detrended_a | seasonal_a |
|---|---|---|---|---|
| 2.252505 | 2010 may. | 2.335101 | -0.0825954 | -0.0047661 |
| 2.268877 | 2010 jun. | 2.325785 | -0.0569078 | -0.0023854 |
| 2.302142 | 2010 jul. | 2.318815 | -0.0166733 | 0.0010789 |
| 2.308080 | 2010 ago. | 2.314956 | -0.0068766 | 0.0021100 |
| 2.297191 | 2010 sep. | 2.309837 | -0.0126460 | 0.0031991 |
| 2.297476 | 2010 oct. | 2.306418 | -0.0089413 | -0.0010349 |
# Parte aleatoria
Elecmensual_20190618.dt.trans[,`:=`( residual_a = detrended_a - seasonal_a)]
knitr::kable(tail(Elecmensual_20190618.dt.trans))| Demand | Month | trend | detrended_a | seasonal_a | residual_a |
|---|---|---|---|---|---|
| 2.252505 | 2010 may. | 2.335101 | -0.0825954 | -0.0047661 | -0.0778292 |
| 2.268877 | 2010 jun. | 2.325785 | -0.0569078 | -0.0023854 | -0.0545223 |
| 2.302142 | 2010 jul. | 2.318815 | -0.0166733 | 0.0010789 | -0.0177522 |
| 2.308080 | 2010 ago. | 2.314956 | -0.0068766 | 0.0021100 | -0.0089866 |
| 2.297191 | 2010 sep. | 2.309837 | -0.0126460 | 0.0031991 | -0.0158451 |
| 2.297476 | 2010 oct. | 2.306418 | -0.0089413 | -0.0010349 | -0.0079065 |
# Gráficas
ggsdc(Elecmensual_20190618.dt.trans,
aes(x = Month, y = Demand),
method = "decompose",
frequency = 12,
s.window = 8,
type = "additive") +
geom_line() +
ggtitle("Aditiva") +
theme_minimal()## Warning in if (class(data[, xvar]) == "Date" & (is.null(frequency))) {: la
## condición tiene longitud > 1 y sólo el primer elemento será usado## Warning: Removed 6 row(s) containing missing values (geom_path).
#¿Es multiplicativa?
ggAcf(Elecmensual_20190618.dt.trans$residual_a)
Elecmensual_20190618.dt.trans$residual_a %>% ur.kpss() %>% summary()##
## #######################
## # KPSS Unit Root Test #
## #######################
##
## Test is of type: mu with 6 lags.
##
## Value of test-statistic is: 0.0547
##
## Critical value for a significance level of:
## 10pct 5pct 2.5pct 1pct
## critical values 0.347 0.463 0.574 0.739- Obtén los datos desestacionalizados y muestra en una tabla los datos originales y los desestacionalizados. Calcula la diferencia entre ellos y gráfica ambas series (original y desestacionalizada) en una gráfica.
comparativa_df <-
data.frame(fecha = yearmonth(
seq(
as.Date("1950-01-01"),
by = "month",
length.out = 730
)
),
Elecmensual_20190618.ts)
comparativa_df$desestacionalizados <-
seasadj(decompose(Elecmensual_20190618.ts, "multiplicative"))
comparativa_df_restas <- dplyr::summarise(comparativa_df,
restas = Demand - desestacionalizados)
comparativa_df <- clean_names(comparativa_df)
comparativa_df_restas <- clean_names(comparativa_df_restas)
comparativa_df <- cbind(comparativa_df, comparativa_df_restas)
knitr::kable(comparativa_df)| fecha | demand | desestacionalizados | restas |
|---|---|---|---|
| 1950 ene. | 174.8963 | 174.9988 | -0.10251801 |
| 1950 feb. | 188.5909 | 187.4366 | 1.15430131 |
| 1950 mar. | 188.9169 | 187.5912 | 1.32570098 |
| 1950 abr. | 173.8142 | 173.1173 | 0.69694883 |
| 1950 may. | 169.5152 | 170.9687 | -1.45354768 |
| 1950 jun. | 195.7288 | 196.6410 | -0.91219118 |
| 1950 jul. | 199.9029 | 199.2454 | 0.65747048 |
| 1950 ago. | 205.3375 | 204.3724 | 0.96508480 |
| 1950 sep. | 228.0782 | 225.9980 | 2.08020819 |
| 1950 oct. | 258.5984 | 258.4784 | 0.12002321 |
| 1950 nov. | 201.7970 | 203.7739 | -1.97689690 |
| 1950 dic. | 187.6298 | 189.8154 | -2.18555976 |
| 1951 ene. | 254.6636 | 254.8129 | -0.14927477 |
| 1951 feb. | 322.2323 | 320.2600 | 1.97227525 |
| 1951 mar. | 343.9934 | 341.5795 | 2.41393114 |
| 1951 abr. | 347.6376 | 346.2437 | 1.39393454 |
| 1951 may. | 332.9455 | 335.8004 | -2.85491896 |
| 1951 jun. | 219.7517 | 220.7758 | -1.02414955 |
| 1951 jul. | 186.9816 | 186.3666 | 0.61497298 |
| 1951 ago. | 228.4876 | 227.4137 | 1.07389011 |
| 1951 sep. | 222.3650 | 220.3369 | 2.02810043 |
| 1951 oct. | 220.4669 | 220.3646 | 0.10232525 |
| 1951 nov. | 240.5806 | 242.9374 | -2.35683901 |
| 1951 dic. | 224.6652 | 227.2822 | -2.61695755 |
| 1952 ene. | 181.1498 | 181.2560 | -0.10618359 |
| 1952 feb. | 182.2231 | 181.1078 | 1.11532615 |
| 1952 mar. | 230.2226 | 228.6070 | 1.61555862 |
| 1952 abr. | 309.3744 | 308.1339 | 1.24050926 |
| 1952 may. | 243.2239 | 245.3095 | -2.08558014 |
| 1952 jun. | 258.3896 | 259.5938 | -1.20422091 |
| 1952 jul. | 259.3053 | 258.4525 | 0.85284196 |
| 1952 ago. | 241.3185 | 240.1843 | 1.13419525 |
| 1952 sep. | 264.5050 | 262.0926 | 2.41244217 |
| 1952 oct. | 264.9556 | 264.8326 | 0.12297378 |
| 1952 nov. | 221.6807 | 223.8524 | -2.17168683 |
| 1952 dic. | 237.1498 | 239.9122 | -2.76238135 |
| 1953 ene. | 276.4134 | 276.5754 | -0.16202373 |
| 1953 feb. | 283.3155 | 281.5814 | 1.73407864 |
| 1953 mar. | 272.5084 | 270.5961 | 1.91229399 |
| 1953 abr. | 243.6298 | 242.6529 | 0.97689086 |
| 1953 may. | 223.0845 | 224.9974 | -1.91289015 |
| 1953 jun. | 238.7871 | 239.9000 | -1.11286375 |
| 1953 jul. | 252.2366 | 251.4070 | 0.82959336 |
| 1953 ago. | 250.9030 | 249.7238 | 1.17924233 |
| 1953 sep. | 242.4558 | 240.2445 | 2.21134042 |
| 1953 oct. | 214.2726 | 214.1731 | 0.09945029 |
| 1953 nov. | 175.2935 | 177.0108 | -1.71725633 |
| 1953 dic. | 216.4104 | 218.9312 | -2.52080353 |
| 1954 ene. | 232.6376 | 232.7740 | -0.13636391 |
| 1954 feb. | 222.3622 | 221.0012 | 1.36100405 |
| 1954 mar. | 210.2031 | 208.7280 | 1.47507425 |
| 1954 abr. | 211.6370 | 210.7884 | 0.84860822 |
| 1954 may. | 186.7995 | 188.4013 | -1.60175595 |
| 1954 jun. | 178.2322 | 179.0628 | -0.83064853 |
| 1954 jul. | 221.6854 | 220.9563 | 0.72911202 |
| 1954 ago. | 237.5595 | 236.4430 | 1.11652798 |
| 1954 sep. | 220.5093 | 218.4981 | 2.01117535 |
| 1954 oct. | 216.7880 | 216.6874 | 0.10061776 |
| 1954 nov. | 214.8875 | 216.9926 | -2.10513750 |
| 1954 dic. | 193.5388 | 195.7932 | -2.25438930 |
| 1955 ene. | 183.3550 | 183.4625 | -0.10747620 |
| 1955 feb. | 228.3825 | 226.9846 | 1.39785227 |
| 1955 mar. | 255.3741 | 253.5820 | 1.79205616 |
| 1955 abr. | 233.9622 | 233.0241 | 0.93812635 |
| 1955 may. | 216.4703 | 218.3265 | -1.85617515 |
| 1955 jun. | 215.9607 | 216.9672 | -1.00648165 |
| 1955 jul. | 194.5699 | 193.9300 | 0.63993052 |
| 1955 ago. | 200.7804 | 199.8367 | 0.94366647 |
| 1955 sep. | 213.9160 | 211.9650 | 1.95104055 |
| 1955 oct. | 240.5818 | 240.4701 | 0.11166117 |
| 1955 nov. | 220.3766 | 222.5355 | -2.15891126 |
| 1955 dic. | 219.1226 | 221.6750 | -2.55239593 |
| 1956 ene. | 223.9310 | 224.0623 | -0.13126041 |
| 1956 feb. | 191.9780 | 190.8030 | 1.17503260 |
| 1956 mar. | 172.9602 | 171.7465 | 1.21372681 |
| 1956 abr. | 212.6693 | 211.8166 | 0.85274747 |
| 1956 may. | 216.7992 | 218.6582 | -1.85899538 |
| 1956 jun. | 215.9562 | 216.9627 | -1.00646068 |
| 1956 jul. | 226.8287 | 226.0827 | 0.74602807 |
| 1956 ago. | 221.9756 | 220.9323 | 1.04328376 |
| 1956 sep. | 186.2491 | 184.5504 | 1.69870204 |
| 1956 oct. | 179.2746 | 179.1914 | 0.08320668 |
| 1956 nov. | 213.5667 | 215.6589 | -2.09219833 |
| 1956 dic. | 214.6133 | 217.1132 | -2.49987045 |
| 1957 ene. | 217.4129 | 217.5403 | -0.12743973 |
| 1957 feb. | 221.7905 | 220.4330 | 1.35750486 |
| 1957 mar. | 214.8814 | 213.3735 | 1.50790365 |
| 1957 abr. | 185.2121 | 184.4694 | 0.74265138 |
| 1957 may. | 181.7951 | 183.3539 | -1.55884455 |
| 1957 jun. | 230.6637 | 231.7387 | -1.07500476 |
| 1957 jul. | 253.2901 | 252.4570 | 0.83305827 |
| 1957 ago. | 235.5289 | 234.4219 | 1.10698417 |
| 1957 sep. | 222.7004 | 220.6692 | 2.03115947 |
| 1957 oct. | 218.9320 | 218.8304 | 0.10161286 |
| 1957 nov. | 192.1518 | 194.0342 | -1.88240805 |
| 1957 dic. | 182.5951 | 184.7220 | -2.12691429 |
| 1958 ene. | 218.4745 | 218.6026 | -0.12806201 |
| 1958 feb. | 226.2018 | 224.8173 | 1.38450494 |
| 1958 mar. | 225.5993 | 224.0162 | 1.58311518 |
| 1958 abr. | 223.8808 | 222.9831 | 0.89770261 |
| 1958 may. | 220.3987 | 222.2886 | -1.88986013 |
| 1958 jun. | 189.7302 | 190.6144 | -0.88423479 |
| 1958 jul. | 180.7974 | 180.2028 | 0.59463346 |
| 1958 ago. | 212.9014 | 211.9008 | 1.00063508 |
| 1958 sep. | 216.1034 | 214.1324 | 1.97099093 |
| 1958 oct. | 218.3603 | 218.2590 | 0.10134751 |
| 1958 nov. | 215.1137 | 217.2211 | -2.10735346 |
| 1958 dic. | 177.7474 | 179.8178 | -2.07044705 |
| 1959 ene. | 183.7940 | 183.9017 | -0.10773353 |
| 1959 feb. | 178.9498 | 177.8545 | 1.09529138 |
| 1959 mar. | 181.3320 | 180.0595 | 1.27247488 |
| 1959 abr. | 219.8456 | 218.9641 | 0.88152253 |
| 1959 may. | 218.9037 | 220.7807 | -1.87704091 |
| 1959 jun. | 217.9708 | 218.9866 | -1.01584969 |
| 1959 jul. | 189.6816 | 189.0577 | 0.62385315 |
| 1959 ago. | 189.3522 | 188.4622 | 0.88995401 |
| 1959 sep. | 186.1761 | 184.4781 | 1.69803624 |
| 1959 oct. | 222.7253 | 222.6219 | 0.10337344 |
| 1959 nov. | 226.8940 | 229.1168 | -2.22275873 |
| 1959 dic. | 227.8383 | 230.4922 | -2.65391862 |
| 1960 ene. | 234.1514 | 234.2887 | -0.13725125 |
| 1960 feb. | 234.8755 | 233.4379 | 1.43759374 |
| 1960 mar. | 205.5938 | 204.1511 | 1.44272906 |
| 1960 abr. | 203.6670 | 202.8503 | 0.81665063 |
| 1960 may. | 237.8857 | 239.9255 | -2.03980650 |
| 1960 jun. | 240.6153 | 241.7367 | -1.12138405 |
| 1960 jul. | 240.3634 | 239.5729 | 0.79054301 |
| 1960 ago. | 241.3502 | 240.2159 | 1.13434424 |
| 1960 sep. | 236.7497 | 234.5904 | 2.15929741 |
| 1960 oct. | 206.3455 | 206.2497 | 0.09577109 |
| 1960 nov. | 192.7160 | 194.6039 | -1.88793521 |
| 1960 dic. | 229.3544 | 232.0260 | -2.67157854 |
| 1961 ene. | 230.0164 | 230.1512 | -0.13482746 |
| 1961 feb. | 224.4637 | 223.0898 | 1.37386662 |
| 1961 mar. | 216.9592 | 215.4367 | 1.52248435 |
| 1961 abr. | 212.6305 | 211.7779 | 0.85259189 |
| 1961 may. | 188.9991 | 190.6197 | -1.62061693 |
| 1961 jun. | 181.5075 | 182.3534 | -0.84591302 |
| 1961 jul. | 217.0623 | 216.3484 | 0.71390688 |
| 1961 ago. | 224.3771 | 223.3225 | 1.05457079 |
| 1961 sep. | 221.9410 | 219.9168 | 2.02423330 |
| 1961 oct. | 222.4899 | 222.3866 | 0.10326418 |
| 1961 nov. | 221.5659 | 223.7365 | -2.17056220 |
| 1961 dic. | 195.6669 | 197.9461 | -2.27917795 |
| 1962 ene. | 190.3111 | 190.4227 | -0.11155362 |
| 1962 feb. | 226.0510 | 224.6674 | 1.38358195 |
| 1962 mar. | 226.9175 | 225.3251 | 1.59236549 |
| 1962 abr. | 230.2927 | 229.3693 | 0.92341263 |
| 1962 may. | 234.6604 | 236.6726 | -2.01215041 |
| 1962 jun. | 231.8486 | 232.9291 | -1.08052697 |
| 1962 jul. | 201.0383 | 200.3771 | 0.66120476 |
| 1962 ago. | 199.7129 | 198.7743 | 0.93864922 |
| 1962 sep. | 232.5876 | 230.4663 | 2.12133659 |
| 1962 oct. | 235.0114 | 234.9023 | 0.10907579 |
| 1962 nov. | 230.9970 | 233.2600 | -2.26295362 |
| 1962 dic. | 232.0875 | 234.7909 | -2.70341439 |
| 1963 ene. | 234.6715 | 234.8091 | -0.13755611 |
| 1963 feb. | 202.4323 | 201.1933 | 1.23901985 |
| 1963 mar. | 196.7197 | 195.3392 | 1.38045616 |
| 1963 abr. | 206.5046 | 205.6766 | 0.82802866 |
| 1963 may. | 235.7782 | 237.7999 | -2.02173525 |
| 1963 jun. | 241.0994 | 242.2230 | -1.12364019 |
| 1963 jul. | 243.6167 | 242.8155 | 0.80124295 |
| 1963 ago. | 237.2126 | 236.0977 | 1.11489755 |
| 1963 sep. | 212.1366 | 210.2018 | 1.93481137 |
| 1963 oct. | 203.3582 | 203.2638 | 0.09438459 |
| 1963 nov. | 241.3206 | 243.6847 | -2.36408839 |
| 1963 dic. | 244.7568 | 247.6078 | -2.85098963 |
| 1964 ene. | 244.5883 | 244.7317 | -0.14336899 |
| 1964 feb. | 252.8974 | 251.3495 | 1.54789971 |
| 1964 mar. | 239.6948 | 238.0128 | 1.68202861 |
| 1964 abr. | 211.0494 | 210.2031 | 0.84625210 |
| 1964 may. | 205.6888 | 207.4525 | -1.76372666 |
| 1964 jun. | 245.3576 | 246.5011 | -1.14348546 |
| 1964 jul. | 261.7745 | 260.9135 | 0.86096303 |
| 1964 ago. | 248.2476 | 247.0808 | 1.16676197 |
| 1964 sep. | 243.3896 | 241.1697 | 2.21985723 |
| 1964 oct. | 241.5915 | 241.4794 | 0.11212981 |
| 1964 nov. | 218.8741 | 221.0183 | -2.14419208 |
| 1964 dic. | 220.2953 | 222.8614 | -2.56605584 |
| 1965 ene. | 255.0056 | 255.1551 | -0.14947524 |
| 1965 feb. | 254.8101 | 253.2505 | 1.55960670 |
| 1965 mar. | 245.0865 | 243.3666 | 1.71986420 |
| 1965 abr. | 247.8669 | 246.8730 | 0.99388051 |
| 1965 may. | 249.0520 | 251.1876 | -2.13555455 |
| 1965 jun. | 218.4067 | 219.4246 | -1.01788119 |
| 1965 jul. | 212.9148 | 212.2145 | 0.70026596 |
| 1965 ago. | 241.2600 | 240.1261 | 1.13392030 |
| 1965 sep. | 242.9725 | 240.7564 | 2.21605303 |
| 1965 oct. | 257.5991 | 257.4795 | 0.11955941 |
| 1965 nov. | 257.9806 | 260.5079 | -2.52729747 |
| 1965 dic. | 247.6547 | 250.5394 | -2.88474510 |
| 1966 ene. | 227.0290 | 227.1621 | -0.13307635 |
| 1966 feb. | 220.9397 | 219.5874 | 1.35229740 |
| 1966 mar. | 258.8287 | 257.0124 | 1.81629839 |
| 1966 abr. | 264.1827 | 263.1234 | 1.05930253 |
| 1966 may. | 253.5232 | 255.6971 | -2.17389390 |
| 1966 jun. | 259.8050 | 261.0158 | -1.21081736 |
| 1966 jul. | 256.2355 | 255.3928 | 0.84274554 |
| 1966 ago. | 223.4825 | 222.4321 | 1.05036618 |
| 1966 sep. | 215.7748 | 213.8068 | 1.96799390 |
| 1966 oct. | 258.8278 | 258.7077 | 0.12012969 |
| 1966 nov. | 268.9846 | 271.6197 | -2.63509775 |
| 1966 dic. | 267.2355 | 270.3483 | -3.11282726 |
| 1967 ene. | 269.3544 | 269.5123 | -0.15788600 |
| 1967 feb. | 253.2748 | 251.7246 | 1.55020965 |
| 1967 mar. | 223.1568 | 221.5908 | 1.56597524 |
| 1967 abr. | 211.2160 | 210.3691 | 0.84692012 |
| 1967 may. | 242.0725 | 244.1482 | -2.07570719 |
| 1967 jun. | 246.4046 | 247.5530 | -1.14836499 |
| 1967 jul. | 237.8841 | 237.1017 | 0.78238872 |
| 1967 ago. | 239.6187 | 238.4925 | 1.12620620 |
| 1967 sep. | 263.3148 | 260.9132 | 2.40158684 |
| 1967 oct. | 227.5769 | 227.4713 | 0.10562521 |
| 1967 nov. | 221.6350 | 223.8062 | -2.17123913 |
| 1967 dic. | 256.6197 | 259.6089 | -2.98917171 |
| 1968 ene. | 250.4816 | 250.6284 | -0.14682343 |
| 1968 feb. | 246.8155 | 245.3048 | 1.51067445 |
| 1968 mar. | 252.0098 | 250.2414 | 1.76844760 |
| 1968 abr. | 243.5690 | 242.5924 | 0.97664707 |
| 1968 may. | 217.1874 | 219.0497 | -1.86232409 |
| 1968 jun. | 212.9136 | 213.9059 | -0.99228068 |
| 1968 jul. | 261.0586 | 260.2000 | 0.85860847 |
| 1968 ago. | 262.4751 | 261.2415 | 1.23363112 |
| 1968 sep. | 253.5156 | 251.2034 | 2.31221234 |
| 1968 oct. | 249.8530 | 249.7370 | 0.11596421 |
| 1968 nov. | 244.9549 | 247.3546 | -2.39969168 |
| 1968 dic. | 221.1463 | 223.7223 | -2.57596850 |
| 1969 ene. | 210.5977 | 210.7211 | -0.12344490 |
| 1969 feb. | 250.2505 | 248.7188 | 1.53169893 |
| 1969 mar. | 248.2650 | 246.5228 | 1.74216893 |
| 1969 abr. | 247.3034 | 246.3118 | 0.99162102 |
| 1969 may. | 242.7937 | 244.8756 | -2.08189129 |
| 1969 jun. | 231.1652 | 232.2425 | -1.07734199 |
| 1969 jul. | 202.5800 | 201.9137 | 0.66627533 |
| 1969 ago. | 200.8607 | 199.9167 | 0.94404388 |
| 1969 sep. | 239.1268 | 236.9458 | 2.18097797 |
| 1969 oct. | 236.9323 | 236.8223 | 0.10996733 |
| 1969 nov. | 233.0740 | 235.3573 | -2.28330088 |
| 1969 dic. | 233.1221 | 235.8376 | -2.71546567 |
| 1970 ene. | 233.8208 | 233.9579 | -0.13705746 |
| 1970 feb. | 193.0105 | 191.8291 | 1.18135219 |
| 1970 mar. | 189.3291 | 188.0005 | 1.32859354 |
| 1970 abr. | 236.2696 | 235.3222 | 0.94737841 |
| 1970 may. | 238.2240 | 240.2667 | -2.04270733 |
| 1970 jun. | 241.4517 | 242.5770 | -1.12528208 |
| 1970 jul. | 241.7054 | 240.9104 | 0.79495678 |
| 1970 ago. | 233.5166 | 232.4191 | 1.09752638 |
| 1970 sep. | 198.1050 | 196.2982 | 1.80683487 |
| 1970 oct. | 186.0104 | 185.9241 | 0.08633296 |
| 1970 nov. | 218.2276 | 220.3655 | -2.13785867 |
| 1970 dic. | 222.7274 | 225.3218 | -2.59438556 |
| 1971 ene. | 222.0213 | 222.1514 | -0.13014101 |
| 1971 feb. | 226.7373 | 225.3495 | 1.38778256 |
| 1971 mar. | 231.3683 | 229.7447 | 1.62359843 |
| 1971 abr. | 196.5834 | 195.7952 | 0.78824728 |
| 1971 may. | 185.0438 | 186.6305 | -1.58670129 |
| 1971 jun. | 225.4641 | 226.5149 | -1.05077210 |
| 1971 jul. | 235.6982 | 234.9230 | 0.77519941 |
| 1971 ago. | 236.1329 | 235.0231 | 1.10982297 |
| 1971 sep. | 241.1509 | 238.9515 | 2.19943896 |
| 1971 oct. | 230.3640 | 230.2571 | 0.10691879 |
| 1971 nov. | 199.8989 | 201.8572 | -1.95830223 |
| 1971 dic. | 187.0570 | 189.2359 | -2.17888764 |
| 1972 ene. | 217.4684 | 217.5959 | -0.12747227 |
| 1972 feb. | 215.1564 | 213.8395 | 1.31689977 |
| 1972 mar. | 215.4661 | 213.9541 | 1.51200671 |
| 1972 abr. | 217.7978 | 216.9245 | 0.87331139 |
| 1972 may. | 214.7996 | 216.6414 | -1.84184934 |
| 1972 jun. | 184.7269 | 185.5878 | -0.86091698 |
| 1972 jul. | 177.3159 | 176.7327 | 0.58318299 |
| 1972 ago. | 207.7305 | 206.7542 | 0.97633189 |
| 1972 sep. | 218.1746 | 216.1847 | 1.98988150 |
| 1972 oct. | 224.6942 | 224.5899 | 0.10428727 |
| 1972 nov. | 224.9024 | 227.1056 | -2.20324810 |
| 1972 dic. | 212.3656 | 214.8393 | -2.47368867 |
| 1973 ene. | 183.7487 | 183.8564 | -0.10770697 |
| 1973 feb. | 173.5839 | 172.5215 | 1.06244852 |
| 1973 mar. | 221.1614 | 219.6094 | 1.55197277 |
| 1973 abr. | 216.7209 | 215.8519 | 0.86899331 |
| 1973 may. | 221.2251 | 223.1220 | -1.89694629 |
| 1973 jun. | 217.7267 | 218.7414 | -1.01471206 |
| 1973 jul. | 213.9397 | 213.2361 | 0.70363681 |
| 1973 ago. | 186.2191 | 185.3439 | 0.87522846 |
| 1973 sep. | 181.4456 | 179.7907 | 1.65489128 |
| 1973 oct. | 222.1222 | 222.0191 | 0.10309352 |
| 1973 nov. | 228.7036 | 230.9441 | -2.24048641 |
| 1973 dic. | 225.6833 | 228.3121 | -2.62881663 |
| 1974 ene. | 224.5799 | 224.7115 | -0.13164077 |
| 1974 feb. | 214.5551 | 213.2419 | 1.31321942 |
| 1974 mar. | 191.7391 | 190.3936 | 1.34550542 |
| 1974 abr. | 183.9389 | 183.2014 | 0.73754619 |
| 1974 may. | 213.2147 | 215.0430 | -1.82825925 |
| 1974 jun. | 222.9096 | 223.9485 | -1.03886689 |
| 1974 jul. | 233.0016 | 232.2353 | 0.76633043 |
| 1974 ago. | 224.6348 | 223.5790 | 1.05578198 |
| 1974 sep. | 227.9454 | 225.8664 | 2.07899698 |
| 1974 oct. | 193.2198 | 193.1301 | 0.08967906 |
| 1974 nov. | 182.9607 | 184.7531 | -1.79236778 |
| 1974 dic. | 212.9383 | 215.4187 | -2.48035962 |
| 1975 ene. | 220.9596 | 221.0891 | -0.12951868 |
| 1975 feb. | 218.7275 | 217.3887 | 1.33875727 |
| 1975 mar. | 218.7459 | 217.2109 | 1.53502230 |
| 1975 abr. | 226.7615 | 225.8522 | 0.90925345 |
| 1975 may. | 187.8364 | 189.4470 | -1.61064709 |
| 1975 jun. | 186.3019 | 187.1702 | -0.86825725 |
| 1975 jul. | 200.5634 | 199.9038 | 0.65964283 |
| 1975 ago. | 186.9384 | 186.0598 | 0.87860916 |
| 1975 sep. | 206.6377 | 204.7530 | 1.88465814 |
| 1975 oct. | 211.9857 | 211.8873 | 0.09838887 |
| 1975 nov. | 227.2132 | 229.4391 | -2.22588577 |
| 1975 dic. | 205.4283 | 207.8212 | -2.39288123 |
| 1976 ene. | 176.0597 | 176.1629 | -0.10319995 |
| 1976 feb. | 211.9239 | 210.6268 | 1.29711473 |
| 1976 mar. | 215.3201 | 213.8091 | 1.51098217 |
| 1976 abr. | 222.2635 | 221.3723 | 0.89121766 |
| 1976 may. | 239.6066 | 241.6612 | -2.05456276 |
| 1976 jun. | 223.6820 | 224.7245 | -1.04246665 |
| 1976 jul. | 189.5637 | 188.9402 | 0.62346538 |
| 1976 ago. | 182.0131 | 181.1576 | 0.85546029 |
| 1976 sep. | 208.3546 | 206.4543 | 1.90031729 |
| 1976 oct. | 211.8105 | 211.7122 | 0.09830756 |
| 1976 nov. | 217.4702 | 219.6006 | -2.13043882 |
| 1976 dic. | 228.7774 | 231.4423 | -2.66485750 |
| 1977 ene. | 215.2890 | 215.4152 | -0.12619478 |
| 1977 feb. | 196.0592 | 194.8592 | 1.20001225 |
| 1977 mar. | 187.2593 | 185.9452 | 1.31406898 |
| 1977 abr. | 222.5512 | 221.6588 | 0.89237127 |
| 1977 may. | 213.9397 | 215.7742 | -1.83447593 |
| 1977 jun. | 218.0656 | 219.0819 | -1.01629150 |
| 1977 jul. | 214.9400 | 214.2331 | 0.70692674 |
| 1977 ago. | 212.5017 | 211.5029 | 0.99875649 |
| 1977 sep. | 193.7848 | 192.0174 | 1.76743209 |
| 1977 oct. | 213.2383 | 213.1393 | 0.09897024 |
| 1977 nov. | 242.4983 | 244.8739 | -2.37562569 |
| 1977 dic. | 232.7346 | 235.4456 | -2.71095197 |
| 1978 ene. | 228.0617 | 228.1954 | -0.13368168 |
| 1978 feb. | 235.9962 | 234.5517 | 1.44445316 |
| 1978 mar. | 224.0923 | 222.5198 | 1.57254000 |
| 1978 abr. | 192.1555 | 191.3850 | 0.77049257 |
| 1978 may. | 185.8437 | 187.4373 | -1.59356021 |
| 1978 jun. | 216.0966 | 217.1037 | -1.00711501 |
| 1978 jul. | 217.0111 | 216.2974 | 0.71373848 |
| 1978 ago. | 219.8595 | 218.8262 | 1.03333810 |
| 1978 sep. | 215.7580 | 213.7902 | 1.96784068 |
| 1978 oct. | 219.1628 | 219.0611 | 0.10171998 |
| 1978 nov. | 209.4520 | 211.5039 | -2.05188882 |
| 1978 dic. | 196.8496 | 199.1426 | -2.29295434 |
| 1979 ene. | 228.2496 | 228.3834 | -0.13379182 |
| 1979 feb. | 231.0967 | 229.6822 | 1.41446498 |
| 1979 mar. | 214.1462 | 212.6435 | 1.50274447 |
| 1979 abr. | 216.3581 | 215.4906 | 0.86753858 |
| 1979 may. | 206.0286 | 207.7952 | -1.76664035 |
| 1979 jun. | 189.0453 | 189.9263 | -0.88104282 |
| 1979 jul. | 204.0398 | 203.3687 | 0.67107654 |
| 1979 ago. | 230.4448 | 229.3617 | 1.08308894 |
| 1979 sep. | 219.4981 | 217.4961 | 2.00195260 |
| 1979 oct. | 192.9426 | 192.8530 | 0.08955040 |
| 1979 nov. | 166.6984 | 168.3315 | -1.63305475 |
| 1979 dic. | 166.8567 | 168.8003 | -1.94358939 |
| 1980 ene. | 173.7280 | 173.8298 | -0.10183319 |
| 1980 feb. | 188.5128 | 187.3590 | 1.15382328 |
| 1980 mar. | 191.2730 | 189.9308 | 1.34223462 |
| 1980 abr. | 186.2401 | 185.4933 | 0.74677339 |
| 1980 may. | 186.3702 | 187.9683 | -1.59807481 |
| 1980 jun. | 186.8963 | 187.7673 | -0.87102744 |
| 1980 jul. | 200.5909 | 199.9312 | 0.65973328 |
| 1980 ago. | 200.9169 | 199.9726 | 0.94430802 |
| 1980 sep. | 185.8142 | 184.1195 | 1.69473550 |
| 1980 oct. | 181.5152 | 181.4310 | 0.08424661 |
| 1980 nov. | 207.7288 | 209.7638 | -2.03500756 |
| 1980 dic. | 211.9029 | 214.3712 | -2.46829902 |
| 1981 ene. | 217.3375 | 217.4649 | -0.12739554 |
| 1981 feb. | 240.0782 | 238.6088 | 1.46943771 |
| 1981 mar. | 270.5984 | 268.6995 | 1.89889080 |
| 1981 abr. | 213.7970 | 212.9397 | 0.85726925 |
| 1981 may. | 199.6298 | 201.3416 | -1.71177235 |
| 1981 jun. | 266.6636 | 267.9064 | -1.24278176 |
| 1981 jul. | 334.2323 | 333.1330 | 1.09927306 |
| 1981 ago. | 355.9934 | 354.3202 | 1.67316647 |
| 1981 sep. | 359.6376 | 356.3575 | 3.28010780 |
| 1981 oct. | 344.9455 | 344.7854 | 0.16009947 |
| 1981 nov. | 231.7517 | 234.0220 | -2.27034701 |
| 1981 dic. | 198.9816 | 201.2994 | -2.31778842 |
| 1982 ene. | 240.4876 | 240.6286 | -0.14096530 |
| 1982 feb. | 234.3650 | 232.9305 | 1.43446914 |
| 1982 mar. | 232.4669 | 230.8356 | 1.63130772 |
| 1982 abr. | 252.5806 | 251.5678 | 1.01278119 |
| 1982 may. | 236.6652 | 238.6945 | -2.02934104 |
| 1982 jun. | 193.1498 | 194.0500 | -0.90017179 |
| 1982 jul. | 194.2231 | 193.5843 | 0.63878991 |
| 1982 ago. | 242.2226 | 241.0842 | 1.13844451 |
| 1982 sep. | 321.3744 | 318.4433 | 2.93112476 |
| 1982 oct. | 255.2239 | 255.1054 | 0.11845701 |
| 1982 nov. | 270.3896 | 273.0385 | -2.64886178 |
| 1982 dic. | 271.3053 | 274.4655 | -3.16023332 |
| 1983 ene. | 253.3185 | 253.4670 | -0.14848632 |
| 1983 feb. | 276.5050 | 274.8126 | 1.69239387 |
| 1983 mar. | 276.9556 | 275.0121 | 1.94350167 |
| 1983 abr. | 233.6807 | 232.7437 | 0.93699761 |
| 1983 may. | 249.1498 | 251.2862 | -2.13639316 |
| 1983 jun. | 288.4134 | 289.7575 | -1.34414638 |
| 1983 jul. | 295.3155 | 294.3442 | 0.97127768 |
| 1983 ago. | 284.5084 | 283.1712 | 1.33718748 |
| 1983 sep. | 255.6298 | 253.2983 | 2.33149509 |
| 1983 oct. | 235.0845 | 234.9754 | 0.10910971 |
| 1983 nov. | 250.7871 | 253.2439 | -2.45682661 |
| 1983 dic. | 264.2366 | 267.3145 | -3.07789530 |
| 1984 ene. | 262.9030 | 263.0571 | -0.15410442 |
| 1984 feb. | 254.4558 | 252.8984 | 1.55743815 |
| 1984 mar. | 226.2726 | 224.6848 | 1.58783998 |
| 1984 abr. | 187.2935 | 186.5425 | 0.75099724 |
| 1984 may. | 228.4104 | 230.3690 | -1.95855833 |
| 1984 jun. | 244.6376 | 245.7777 | -1.14012992 |
| 1984 jul. | 234.3622 | 233.5914 | 0.77080537 |
| 1984 ago. | 222.2031 | 221.1587 | 1.04435301 |
| 1984 sep. | 223.6370 | 221.5973 | 2.03970182 |
| 1984 oct. | 198.7995 | 198.7072 | 0.09226876 |
| 1984 nov. | 190.2322 | 192.0958 | -1.86360276 |
| 1984 dic. | 233.6854 | 236.4074 | -2.72202714 |
| 1985 ene. | 249.5595 | 249.7058 | -0.14628293 |
| 1985 feb. | 232.5093 | 231.0862 | 1.42311102 |
| 1985 mar. | 228.7880 | 227.1825 | 1.60549149 |
| 1985 abr. | 226.8875 | 225.9777 | 0.90975868 |
| 1985 may. | 205.5388 | 207.3012 | -1.76244045 |
| 1985 jun. | 195.3550 | 196.2654 | -0.91044909 |
| 1985 jul. | 240.3825 | 239.5919 | 0.79060583 |
| 1985 ago. | 267.3741 | 266.1174 | 1.25665639 |
| 1985 sep. | 245.9622 | 243.7189 | 2.24332086 |
| 1985 oct. | 228.4703 | 228.3643 | 0.10603987 |
| 1985 nov. | 227.9607 | 230.1939 | -2.23320862 |
| 1985 dic. | 206.5699 | 208.9761 | -2.40617888 |
| 1986 ene. | 212.7804 | 212.9051 | -0.12472433 |
| 1986 feb. | 225.9160 | 224.5332 | 1.38275566 |
| 1986 mar. | 252.5818 | 250.8093 | 1.77246154 |
| 1986 abr. | 232.3766 | 231.4448 | 0.93176851 |
| 1986 may. | 231.1226 | 233.1044 | -1.98181472 |
| 1986 jun. | 235.9310 | 237.0306 | -1.09955293 |
| 1986 jul. | 203.9780 | 203.3071 | 0.67087328 |
| 1986 ago. | 184.9602 | 184.0909 | 0.86931164 |
| 1986 sep. | 224.6693 | 222.6202 | 2.04911701 |
| 1986 oct. | 228.7992 | 228.6930 | 0.10619252 |
| 1986 nov. | 227.9562 | 230.1894 | -2.23316454 |
| 1986 dic. | 238.8287 | 241.6106 | -2.78193761 |
| 1987 ene. | 233.9756 | 234.1127 | -0.13714820 |
| 1987 feb. | 198.2491 | 197.0357 | 1.21341589 |
| 1987 mar. | 191.2746 | 189.9324 | 1.34224585 |
| 1987 abr. | 225.5667 | 224.6622 | 0.90446262 |
| 1987 may. | 226.6133 | 228.5564 | -1.94314867 |
| 1987 jun. | 229.4129 | 230.4821 | -1.06917543 |
| 1987 jul. | 233.7905 | 233.0216 | 0.76892508 |
| 1987 ago. | 226.8814 | 225.8151 | 1.06634098 |
| 1987 sep. | 197.2121 | 195.4134 | 1.79869109 |
| 1987 oct. | 193.7951 | 193.7052 | 0.08994607 |
| 1987 nov. | 242.6637 | 245.0409 | -2.37724602 |
| 1987 dic. | 265.2901 | 268.3803 | -3.09016674 |
| 1988 ene. | 247.5289 | 247.6740 | -0.14509266 |
| 1988 feb. | 234.7004 | 233.2639 | 1.43652201 |
| 1988 mar. | 230.9320 | 229.3115 | 1.62053675 |
| 1988 abr. | 204.1518 | 203.3332 | 0.81859455 |
| 1988 may. | 194.5951 | 196.2637 | -1.66860114 |
| 1988 jun. | 230.4745 | 231.5486 | -1.07412300 |
| 1988 jul. | 238.2018 | 237.4184 | 0.78343362 |
| 1988 ago. | 237.5993 | 236.4826 | 1.11671504 |
| 1988 sep. | 235.8808 | 233.7294 | 2.15137252 |
| 1988 oct. | 232.3987 | 232.2908 | 0.10786315 |
| 1988 nov. | 201.7302 | 203.7064 | -1.97624249 |
| 1988 dic. | 192.7974 | 195.0432 | -2.24575328 |
| 1989 ene. | 224.9014 | 225.0332 | -0.13182923 |
| 1989 feb. | 228.1034 | 226.7073 | 1.39614400 |
| 1989 mar. | 230.3603 | 228.7438 | 1.61652491 |
| 1989 abr. | 227.1137 | 226.2030 | 0.91066568 |
| 1989 may. | 189.7474 | 191.3744 | -1.62703340 |
| 1989 jun. | 195.7940 | 196.7065 | -0.91249504 |
| 1989 jul. | 190.9498 | 190.3218 | 0.62802419 |
| 1989 ago. | 193.3320 | 192.4233 | 0.90865904 |
| 1989 sep. | 231.8456 | 229.7310 | 2.11456911 |
| 1989 oct. | 230.9037 | 230.7965 | 0.10716928 |
| 1989 nov. | 229.9708 | 232.2237 | -2.25290049 |
| 1989 dic. | 201.6816 | 204.0308 | -2.34923871 |
| 1990 ene. | 201.3522 | 201.4702 | -0.11802552 |
| 1990 feb. | 198.1761 | 196.9631 | 1.21296908 |
| 1990 mar. | 234.7253 | 233.0781 | 1.64715576 |
| 1990 abr. | 238.8940 | 237.9361 | 0.95790156 |
| 1990 may. | 239.8383 | 241.8948 | -2.05654952 |
| 1990 jun. | 246.1514 | 247.2986 | -1.14718496 |
| 1990 jul. | 246.8755 | 246.0635 | 0.81196098 |
| 1990 ago. | 217.5938 | 216.5711 | 1.02268933 |
| 1990 sep. | 215.6670 | 213.7000 | 1.96701070 |
| 1990 oct. | 249.8857 | 249.7697 | 0.11597939 |
| 1990 nov. | 252.6153 | 255.0900 | -2.47473651 |
| 1990 dic. | 252.3634 | 255.3030 | -2.93959324 |
| 1991 ene. | 253.3502 | 253.4987 | -0.14850490 |
| 1991 feb. | 248.7497 | 247.2272 | 1.52251304 |
| 1991 mar. | 218.3455 | 216.8133 | 1.53221254 |
| 1991 abr. | 204.7160 | 203.8951 | 0.82085685 |
| 1991 may. | 241.3544 | 243.4239 | -2.06954968 |
| 1991 jun. | 242.0164 | 243.1443 | -1.12791385 |
| 1991 jul. | 236.4637 | 235.6860 | 0.77771710 |
| 1991 ago. | 228.9592 | 227.8831 | 1.07610663 |
| 1991 sep. | 224.6305 | 222.5817 | 2.04876313 |
| 1991 oct. | 200.9991 | 200.9058 | 0.09328966 |
| 1991 nov. | 193.5075 | 195.4032 | -1.89568911 |
| 1991 dic. | 229.0623 | 231.7305 | -2.66817609 |
| 1992 ene. | 236.3771 | 236.5157 | -0.13855587 |
| 1992 feb. | 233.9410 | 232.5091 | 1.43187398 |
| 1992 mar. | 234.4899 | 232.8444 | 1.64550387 |
| 1992 abr. | 233.5659 | 232.6294 | 0.93653729 |
| 1992 may. | 207.6669 | 209.4476 | -1.78068834 |
| 1992 jun. | 202.3111 | 203.2540 | -0.94286789 |
| 1992 jul. | 238.0510 | 237.2681 | 0.78293765 |
| 1992 ago. | 238.9175 | 237.7946 | 1.12291057 |
| 1992 sep. | 242.2927 | 240.0828 | 2.20985285 |
| 1992 oct. | 246.6604 | 246.5459 | 0.11448243 |
| 1992 nov. | 243.8486 | 246.2375 | -2.38885385 |
| 1992 dic. | 213.0383 | 215.5198 | -2.48152445 |
| 1993 ene. | 211.7129 | 211.8370 | -0.12409860 |
| 1993 feb. | 244.5876 | 243.0906 | 1.49703823 |
| 1993 mar. | 247.0114 | 245.2780 | 1.73337195 |
| 1993 abr. | 242.9970 | 242.0226 | 0.97435350 |
| 1993 may. | 244.0875 | 246.1805 | -2.09298528 |
| 1993 jun. | 246.6715 | 247.8211 | -1.14960888 |
| 1993 jul. | 214.4323 | 213.7270 | 0.70525694 |
| 1993 ago. | 208.7197 | 207.7387 | 0.98098112 |
| 1993 sep. | 218.5046 | 216.5117 | 1.99289129 |
| 1993 oct. | 247.7782 | 247.6632 | 0.11500124 |
| 1993 nov. | 253.0994 | 255.5789 | -2.47947897 |
| 1993 dic. | 255.6167 | 258.5942 | -2.97748851 |
| 1994 ene. | 249.2126 | 249.3587 | -0.14607959 |
| 1994 feb. | 224.1366 | 222.7647 | 1.37186455 |
| 1994 mar. | 215.3582 | 213.8470 | 1.51124953 |
| 1994 abr. | 253.3206 | 252.3049 | 1.01574840 |
| 1994 may. | 256.7568 | 258.9584 | -2.20162115 |
| 1994 jun. | 256.5883 | 257.7841 | -1.19582598 |
| 1994 jul. | 264.8974 | 264.0262 | 0.87123409 |
| 1994 ago. | 251.6948 | 250.5118 | 1.18296379 |
| 1994 sep. | 223.0494 | 221.0151 | 2.03434256 |
| 1994 oct. | 217.6888 | 217.5878 | 0.10103585 |
| 1994 nov. | 257.3576 | 259.8788 | -2.52119427 |
| 1994 dic. | 273.7745 | 276.9635 | -3.18899520 |
| 1995 ene. | 260.2476 | 260.4001 | -0.15254792 |
| 1995 feb. | 255.3896 | 253.8264 | 1.56315363 |
| 1995 mar. | 253.5915 | 251.8120 | 1.77954698 |
| 1995 abr. | 230.8741 | 229.9484 | 0.92574389 |
| 1995 may. | 232.2953 | 234.2872 | -1.99187031 |
| 1995 jun. | 267.0056 | 268.2500 | -1.24437565 |
| 1995 jul. | 266.8101 | 265.9326 | 0.87752487 |
| 1995 ago. | 257.0865 | 255.8782 | 1.20830474 |
| 1995 sep. | 259.8669 | 257.4968 | 2.37013996 |
| 1995 oct. | 261.0520 | 260.9308 | 0.12116200 |
| 1995 nov. | 230.4067 | 232.6639 | -2.25717077 |
| 1995 dic. | 224.9148 | 227.5347 | -2.61986495 |
| 1996 ene. | 253.2600 | 253.4085 | -0.14845203 |
| 1996 feb. | 254.9725 | 253.4119 | 1.56060070 |
| 1996 mar. | 269.5991 | 267.7072 | 1.89187834 |
| 1996 abr. | 269.9806 | 268.8980 | 1.08255058 |
| 1996 may. | 259.6547 | 261.8812 | -2.22646988 |
| 1996 jun. | 239.0290 | 240.1430 | -1.11399112 |
| 1996 jul. | 232.9397 | 232.1736 | 0.76612684 |
| 1996 ago. | 270.8287 | 269.5558 | 1.27289298 |
| 1996 sep. | 276.1827 | 273.6638 | 2.51894971 |
| 1996 oct. | 265.5232 | 265.4000 | 0.12323722 |
| 1996 nov. | 271.8050 | 274.4677 | -2.66272770 |
| 1996 dic. | 268.2355 | 271.3600 | -3.12447551 |
| 1997 ene. | 235.4825 | 235.6205 | -0.13803149 |
| 1997 feb. | 227.7748 | 226.3807 | 1.39413275 |
| 1997 mar. | 270.8278 | 268.9273 | 1.90050059 |
| 1997 abr. | 280.9846 | 279.8579 | 1.12667370 |
| 1997 may. | 279.2355 | 281.6299 | -2.39437002 |
| 1997 jun. | 281.3544 | 282.6656 | -1.31124802 |
| 1997 jul. | 265.2748 | 264.4023 | 0.87247534 |
| 1997 ago. | 235.1568 | 234.0516 | 1.10523530 |
| 1997 sep. | 223.2160 | 221.1801 | 2.03586205 |
| 1997 oct. | 254.0725 | 253.9546 | 0.11792261 |
| 1997 nov. | 258.4046 | 260.9361 | -2.53145117 |
| 1997 dic. | 249.8841 | 252.7948 | -2.91071372 |
| 1998 ene. | 251.6187 | 251.7662 | -0.14748996 |
| 1998 feb. | 275.3148 | 273.6297 | 1.68510906 |
| 1998 mar. | 239.5769 | 237.8957 | 1.68120126 |
| 1998 abr. | 233.6350 | 232.6982 | 0.93681436 |
| 1998 may. | 268.6197 | 270.9230 | -2.30334236 |
| 1998 jun. | 262.4816 | 263.7049 | -1.22329161 |
| 1998 jul. | 258.8155 | 257.9643 | 0.85123103 |
| 1998 ago. | 264.0098 | 262.7690 | 1.24084420 |
| 1998 sep. | 255.5690 | 253.2381 | 2.33094056 |
| 1998 oct. | 229.1874 | 229.0810 | 0.10637269 |
| 1998 nov. | 224.9136 | 227.1170 | -2.20335782 |
| 1998 dic. | 273.0586 | 276.2393 | -3.18065621 |
| 1999 ene. | 274.4751 | 274.6360 | -0.16088757 |
| 1999 feb. | 265.5156 | 263.8905 | 1.62513146 |
| 1999 mar. | 261.8530 | 260.0155 | 1.83752104 |
| 1999 abr. | 256.9549 | 255.9246 | 1.03032097 |
| 1999 may. | 233.1463 | 235.1455 | -1.99916741 |
| 1999 jun. | 222.5977 | 223.6351 | -1.03741329 |
| 1999 jul. | 262.2505 | 261.3880 | 0.86252857 |
| 1999 ago. | 260.2650 | 259.0418 | 1.22324367 |
| 1999 sep. | 259.3034 | 256.9384 | 2.36500050 |
| 1999 oct. | 254.7937 | 254.6754 | 0.11825734 |
| 1999 nov. | 243.1652 | 245.5474 | -2.38215895 |
| 1999 dic. | 214.5800 | 217.0795 | -2.49948256 |
| 2000 ene. | 212.8607 | 212.9855 | -0.12477140 |
| 2000 feb. | 251.1268 | 249.5897 | 1.53706246 |
| 2000 mar. | 248.9323 | 247.1854 | 1.74685162 |
| 2000 abr. | 245.0740 | 244.0913 | 0.98268172 |
| 2000 may. | 245.1221 | 247.2240 | -2.10185670 |
| 2000 jun. | 245.8208 | 246.9664 | -1.14564420 |
| 2000 jul. | 205.0105 | 204.3362 | 0.67426912 |
| 2000 ago. | 201.3291 | 200.3829 | 0.94624535 |
| 2000 sep. | 248.2696 | 246.0052 | 2.26436571 |
| 2000 oct. | 250.2240 | 250.1079 | 0.11613641 |
| 2000 nov. | 253.4517 | 255.9346 | -2.48293027 |
| 2000 dic. | 253.7054 | 256.6606 | -2.95522520 |
| 2001 ene. | 245.5166 | 245.6605 | -0.14391313 |
| 2001 feb. | 210.1050 | 208.8190 | 1.28598186 |
| 2001 mar. | 198.0104 | 196.6209 | 1.38951349 |
| 2001 abr. | 230.2276 | 229.3044 | 0.92315159 |
| 2001 may. | 234.7274 | 236.7401 | -2.01272492 |
| 2001 jun. | 234.0213 | 235.1120 | -1.09065281 |
| 2001 jul. | 238.7373 | 237.9521 | 0.78519485 |
| 2001 ago. | 243.3683 | 242.2245 | 1.14382930 |
| 2001 sep. | 208.5834 | 206.6810 | 1.90240408 |
| 2001 oct. | 197.0438 | 196.9523 | 0.09145389 |
| 2001 nov. | 237.4641 | 239.7904 | -2.32630833 |
| 2001 dic. | 247.6982 | 250.5835 | -2.88525180 |
| 2002 ene. | 248.1329 | 248.2783 | -0.14544671 |
| 2002 feb. | 253.1509 | 251.6014 | 1.54945130 |
| 2002 mar. | 242.3640 | 240.6632 | 1.70075939 |
| 2002 abr. | 211.8989 | 211.0492 | 0.84965837 |
| 2002 may. | 199.0570 | 200.7639 | -1.70686074 |
| 2002 jun. | 229.4684 | 230.5378 | -1.06943408 |
| 2002 jul. | 227.1564 | 226.4093 | 0.74710586 |
| 2002 ago. | 227.4661 | 226.3970 | 1.06908907 |
| 2002 sep. | 229.7978 | 227.7019 | 2.09589196 |
| 2002 oct. | 226.7996 | 226.6943 | 0.10526444 |
| 2002 nov. | 196.7269 | 198.6541 | -1.92722785 |
| 2002 dic. | 189.3159 | 191.5211 | -2.20519988 |
| 2003 ene. | 219.7305 | 219.8593 | -0.12879823 |
| 2003 feb. | 230.1746 | 228.7658 | 1.40882111 |
| 2003 mar. | 236.6942 | 235.0332 | 1.66097227 |
| 2003 abr. | 236.9024 | 235.9525 | 0.94991577 |
| 2003 may. | 224.3656 | 226.2895 | -1.92387524 |
| 2003 jun. | 195.7487 | 196.6610 | -0.91228392 |
| 2003 jul. | 185.5839 | 184.9735 | 0.61037602 |
| 2003 ago. | 233.1614 | 232.0655 | 1.09585694 |
| 2003 sep. | 228.7209 | 226.6348 | 2.08607000 |
| 2003 oct. | 233.2251 | 233.1169 | 0.10824671 |
| 2003 nov. | 229.7267 | 231.9772 | -2.25050918 |
| 2003 dic. | 225.9397 | 228.5715 | -2.63180325 |
| 2004 ene. | 198.2191 | 198.3353 | -0.11618901 |
| 2004 feb. | 193.4456 | 192.2616 | 1.18401529 |
| 2004 mar. | 234.1222 | 232.4793 | 1.64292358 |
| 2004 abr. | 240.7036 | 239.7384 | 0.96515757 |
| 2004 may. | 237.6833 | 239.7214 | -2.03807097 |
| 2004 jun. | 236.5799 | 237.6825 | -1.10257712 |
| 2004 jul. | 226.5551 | 225.8100 | 0.74512822 |
| 2004 ago. | 203.7391 | 202.7815 | 0.95757234 |
| 2004 sep. | 195.9389 | 194.1518 | 1.78707875 |
| 2004 oct. | 225.2147 | 225.1102 | 0.10452885 |
| 2004 nov. | 234.9096 | 237.2109 | -2.30128327 |
| 2004 dic. | 245.0016 | 247.8554 | -2.85384112 |
| 2005 ene. | 236.6348 | 236.7735 | -0.13870693 |
| 2005 feb. | 239.9454 | 238.4768 | 1.46862488 |
| 2005 mar. | 205.2198 | 203.7797 | 1.44010456 |
| 2005 abr. | 194.9607 | 194.1790 | 0.78174068 |
| 2005 may. | 224.9383 | 226.8671 | -1.92878599 |
| 2005 jun. | 232.9596 | 234.0453 | -1.08570477 |
| 2005 jul. | 230.7275 | 229.9686 | 0.75885103 |
| 2005 ago. | 230.7459 | 229.6614 | 1.08450411 |
| 2005 sep. | 238.7615 | 236.5839 | 2.17764621 |
| 2005 oct. | 199.8364 | 199.7436 | 0.09275002 |
| 2005 nov. | 198.3019 | 200.2446 | -1.94265728 |
| 2005 dic. | 212.5634 | 215.0394 | -2.47599269 |
| 2006 ene. | 198.9384 | 199.0550 | -0.11661064 |
| 2006 feb. | 218.6377 | 217.2995 | 1.33820764 |
| 2006 mar. | 223.9857 | 222.4139 | 1.57179194 |
| 2006 abr. | 239.2132 | 238.2540 | 0.95918146 |
| 2006 may. | 217.4283 | 219.2927 | -1.86438975 |
| 2006 jun. | 188.0597 | 188.9361 | -0.87644945 |
| 2006 jul. | 223.9239 | 223.1874 | 0.73647433 |
| 2006 ago. | 227.3201 | 226.2517 | 1.06840287 |
| 2006 sep. | 234.2635 | 232.1269 | 2.13662179 |
| 2006 oct. | 251.6066 | 251.4898 | 0.11677811 |
| 2006 nov. | 235.6820 | 237.9909 | -2.30885005 |
| 2006 dic. | 201.5637 | 203.9116 | -2.34786538 |
| 2007 ene. | 194.0131 | 194.1268 | -0.11372360 |
| 2007 feb. | 220.3546 | 219.0059 | 1.34871620 |
| 2007 mar. | 223.8105 | 222.2399 | 1.57056250 |
| 2007 abr. | 229.4702 | 228.5501 | 0.92011462 |
| 2007 may. | 240.7774 | 242.8420 | -2.06460206 |
| 2007 jun. | 227.2890 | 228.3483 | -1.05927702 |
| 2007 jul. | 208.0592 | 207.3749 | 0.68429614 |
| 2007 ago. | 199.2593 | 198.3228 | 0.93651731 |
| 2007 sep. | 234.5512 | 232.4120 | 2.13924579 |
| 2007 oct. | 225.9397 | 225.8348 | 0.10486534 |
| 2007 nov. | 230.0656 | 232.3194 | -2.25382920 |
| 2007 dic. | 226.9400 | 229.5835 | -2.64345500 |
| 2008 ene. | 224.5017 | 224.6333 | -0.13159494 |
| 2008 feb. | 205.7848 | 204.5253 | 1.25953937 |
| 2008 mar. | 225.2383 | 223.6577 | 1.58058191 |
| 2008 abr. | 254.4983 | 253.4778 | 1.02047066 |
| 2008 may. | 244.7346 | 246.8331 | -2.09853399 |
| 2008 jun. | 240.0617 | 241.1805 | -1.11880400 |
| 2008 jul. | 247.9962 | 247.1806 | 0.81564690 |
| 2008 ago. | 236.0923 | 234.9827 | 1.10963215 |
| 2008 sep. | 204.1555 | 202.2935 | 1.86201901 |
| 2008 oct. | 197.8437 | 197.7519 | 0.09182515 |
| 2008 nov. | 228.0966 | 230.3311 | -2.23453996 |
| 2008 dic. | 229.0111 | 231.6787 | -2.66757970 |
| 2009 ene. | 231.8595 | 231.9954 | -0.13590782 |
| 2009 feb. | 227.7580 | 226.3640 | 1.39402992 |
| 2009 mar. | 231.1628 | 229.5406 | 1.62215636 |
| 2009 abr. | 221.4520 | 220.5640 | 0.88796376 |
| 2009 may. | 208.8496 | 210.6404 | -1.79082968 |
| 2009 jun. | 240.2496 | 241.3693 | -1.11967971 |
| 2009 jul. | 243.0967 | 242.2972 | 0.79953270 |
| 2009 ago. | 226.1462 | 225.0833 | 1.06288555 |
| 2009 sep. | 228.3581 | 226.2753 | 2.08276105 |
| 2009 oct. | 218.0286 | 217.9274 | 0.10119356 |
| 2009 nov. | 201.0453 | 203.0148 | -1.96953289 |
| 2009 dic. | 216.0398 | 218.5563 | -2.51648669 |
| 2010 ene. | 242.4448 | 242.5869 | -0.14211255 |
| 2010 feb. | 231.4981 | 230.0812 | 1.41692181 |
| 2010 mar. | 204.9426 | 203.5044 | 1.43815935 |
| 2010 abr. | 178.6984 | 177.9819 | 0.71653317 |
| 2010 may. | 178.8567 | 180.3903 | -1.53364855 |
| 2010 jun. | 185.7280 | 186.5936 | -0.86558260 |
| 2010 jul. | 200.5128 | 199.8533 | 0.65947641 |
| 2010 ago. | 203.2730 | 202.3176 | 0.95538167 |
| 2010 sep. | 198.2401 | 196.4320 | 1.80806706 |
| 2010 oct. | 198.3702 | 198.2781 | 0.09206951 |
Elecmensual_20190618.ts2 <-
ts(
Elecmensual_20190618.xls$Demand,
start = c(1950,1),
deltat = 1/12
)
fit <- stl(Elecmensual_20190618.ts2, s.window = 7)
autoplot(Elecmensual_20190618.ts, series = "Originales") +
autolayer(seasadj(fit),
series = "Datos desestacionalizados")